Enterprise Ontology Research Articles

Enterprise ontologies: Review and an activity theory approach

This paper provides an alternative, theory-based approach for generating an enterprise ontology, using activity theory. Activity theory, based on psychology, provides a template-based approach in capturing the context of individual activity in an organization. In particular, activity theory uses eight key class concepts: activity, outcome, subject, object, community, rules, tools and division of labor, as a means of organizing and capturing context information. Activity theory is compared with other previously proposed enterprise ontologies, including “ARIS,” “REA,” “The Enterprise Ontology,” “TOVE,” and “Enterprise Ontology.” This activity theory approach is found to consider information typically not included in enterprise ontologies, but likely of interest in most any enterprise.

MENTOR: an enabler for interoperable intelligent systems

A community with knowledge organisation based on ontologies will enable an increase in the computational intelligence of its information systems. However, due to the worldwide diversity of communities, a high number of knowledge representation elements, which are not semantically coincident, have appeared representing the same segment of reality, becoming a barrier to business communications. Even if a domain community uses the same kind of technologies in its information systems, such as ontologies, it doesn't solve its semantics differences. In order to solve this interoperability problem, a solution is to use a reference ontology as an intermediary in the communications between the community enterprises and the outside, while allowing the enterprises to keep their own ontology and semantics unchanged internally. This work proposes MENTOR, a methodology to support the development of a common reference ontology for a group of organisations sharing the same business domain. This methodology is based on the mediator ontology (MO) concept, which assists the semantic transformations among each enterprise's ontology and the referential one. The MO enables each organisation to keep its own terminology, glossary and ontological structures, while providing seamless communication and interaction with the others.

Knowledge cultivating for intelligent decision making in small & middle businesses

Small and middle businesses (SMBs) are playing an increasingly important role, but their decision making process mostly relies on skilled employees which are usually inadequate. Based on information systems, data mining and Extension Theory (Extenics), we present a knowledge cultivating method and design a knowledge management platform for improve decision making quality. Through divergence analysis, correlation analysis, and implication analysis, a flow chart of knowledge cultivating algorithm has been designed, and an intelligent knowledge management platform has been developed. By collecting knowledge or information from conditions and the goal, we choose several knowledge as seed, then distribute it to all the department leaders, let them input relative knowledge including data mining knowledge to the platform. The platform then connects them into a knowledge tree with Human-Computer Interaction and enterprise ontology techniques intelligently. From the knowledge tree, we can find the problem solving map and guide the managers in SBMs to take actions by scanning all possible paths. The application in a food company proved its practicality value.

Ontology-based Enterprise Content Retrieval Method

As the traditional way of information retrieval is based on keywords that the computer cannot understand users’ potential semantic and personalized query requirements, an ontology-based method of the enterprise content retrieval is studied in this paper. The architecture of the ontology-based enterprise content retrieval model is proposed and the retrieval process is discussed. Take the electronic products distributing company as an example, the enterprise ontology is set up and an ontology-based semantic retrieval algorithm is designed, which provides a reference for content retrieval in the enterprises.

Enterprise Ontologies for Planning and Integration of Business: A Pragmatic Approach

Enterprise ontologies (EOs), introduced in the mid 1990s, were expected to have a significant impact on enterprise computing, especially integration. However, despite a great deal of academic research on EOs, the actual use of EOs in real-life integration and planning projects is almost nonexisting. This paper describes an approach to build and use EOs for information system (IS) planning and integration projects with particular focus on real-life eBusiness applications. The approach is based on firsthand practical insights gained through construction and use of an IS planning and integration environment that needs to capture business processes, enterprise applications, integration technologies, and computer-communication platforms. The planning model with the aforementioned information is based on an EO and is populated by a set of intelligent advisors while they guide the users through various stages of the planning process. This ontology has been used to support over 40 real-life business scenarios in the telecom, manufacturing, financial services, retail, healthcare, and insurance industries. The practical contribution of this paper is that it connects ontologies to the practice of IS planning and integration, links ontologies to decisions such as enterprise application selection, and provides tools for automatically creating and maintaining ontology repositories.

The Use of the Concept of Event in Enterprise Ontologies and Requirements Engineering Literature

The concept of event is used in a lot of meanings. It can be the possible outcome of doing something (probability theory), it can be a business transaction (accounting), or just a plain happening. In software engineering, the concept of event is also used a lot. It is used to accomplish loose coupling between software components or to realise interaction between different services. There is however not a consensus on the meaning of 'an event'. In enterprise ontologies, an event is defined as a happening at one point in time, or as an activity which takes time to complete. In requirement engineering, the same different uses can be found, together with an event as a request for something that needs to be done. These differences can also be found in implementation. All these distinct purposes of the word event make it diffcult to integrate and use different requirement engineering techniques. Comparison or transformations between models drawn in different grammars is impossible because of the ambiguity of the concept of event. We define three meanings for an event that are used by enterprise ontologies and requirement engineering techniques: an achievement (happening at one point in time), an activity (happening over time) and a request (a demand for something that needs to be done). We also identify a missing link between real economic events, the events defined in the requirements model and the events used in implementation.

Model Driven Interoperability through Semantic Annotations using SoaML and ODM

Abstract Enterprise Interoperability is increasingly being enabled by use of service oriented architectures for the IT systems involved. A combined use of enterprise models, ontologies and service models can facilitate better semantic interoperability of the services being provided and requested. The focus of this paper is to show that service interoperability can be supported through a model driven approach with service oriented systems being described with service models (in SoaML) with semantic annotations to and from ontology models (in ODM)

Process-centered knowledge model and enterprise ontology for the development of knowledge management system

Among many enterprise assets, knowledge is treated as a critical driving force for attaining enterprise performance goals. This is because knowledge facilitates the better business decision makings in a timely fashion. However, since knowledge is created and utilized during the execution of business processes, if knowledge is separated from the business process context, it does not lead to the ability to take the right action for target performance.This paper proposes the framework for process-centered knowledge model and enterprise ontology for the context-rich and networked knowledge storage and retrieval required during task execution. The enterprise knowledge object for a process-centered knowledge model is classified into two types: process knowledge and task support knowledge. In the proposed enterprise ontology, which represents major enterprise concepts, and the relationships between them, all domain concepts are related to the “process” concept, both directly and indirectly. As a result, networked and sophisticated knowledge, rather than single-level knowledge, is provided to the participant of unit activity.In order to show the applicability of the proposed framework, a process-centered KMS (knowledge management system) was also developed, which is classified into 3 parts: (1) project management sub-system based on process knowledge. (2) Knowledge management sub-system for maintaining task support knowledge. (3) Infrastructure sub-system which supports the above two sub-systems.

Positioning and Formalizing the REA Enterprise Ontology

ABSTRACT: Recent Resource, Event, Agent (REA) research has focused on defining and theoretically justifying the ontology's contents. Here, we elaborate on more practical issues related to REA. First, we classify REA and its applications using ontology classification schemes and application frameworks. This analysis clarifies REA's application potential but also reveals weaknesses that may impede its operationalization. Next, we propose a new REA ontology specification that uses a Unified Modeling Language (UML) profile for graphically representing ontologies. This new specification is more complete and precise than previously available specifications, without compromising understandability. It can easily be transformed into a machine-readable representation for automatic processing, which is a prerequisite for the successful application of REA in business modeling, software engineering, knowledge representation, and interoperability creation. The paper ends with a proof of concept application in which a formal Ontology Web Language (OWL) specification of REA is fed into the Prote´ge´ knowledge representation tool and subsequently used for the development of an enterprise schema.

Automating REA Policy Level Specifications with Semantic Web Technologies

ABSTRACT: Enterprise modelers require tools and techniques that consistently represent and logically apply domain knowledge. Current modeling approaches rely on entity relationship or unified modeling diagrams to represent semantic descriptions of business exchanges. However, it remains difficult to transform the implicit metadata, ontologies, and logic embedded in diagrams into a coherent form that can be interpreted by machines and delivered across the web. This study explores the uniting of machine processing capabilities of semantic web technologies with resource event agent (REA) enterprise ontologies to model complex multienterprise partnerships. Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) were used to model REA policies for a distributed e-commerce partnership selling nearly new vehicles. We combine a specialized REA application ontology with semantic technologies to direct multienterprise collaborations. We present a prototype that encodes the ontology's concepts within OWL and SWRL and explore these machine-readable representations within the context of a case study.

OntoDLV: An ASP-based System for Enterprise Ontologies

Enterprise/Corporate ontologies are widely adopted to conceptualize business enterprise information. In this area, the semantic peculiarities of Answer Set Programming (ASP), like the Closed World Assumption (CWA) and the Unique Name Assumption (UNA), are more appropriate than the Ontology Web Language (OWL) assumptions, also because such ontologies frequently stem from relational databases, where both CWA and UNA are adopted. This article presents OntoDLV, a system based on ASP for the specification and reasoning on enterprise ontologies. OntoDLV implements a powerful ontology representation language, called OntoDLP, extending (disjunctive) ASP with all the main ontology features including classes, inheritance, relations and axioms. OntoDLP is strongly typed, and includes also complex type constructors, like lists and sets. Importantly, OntoDLV supports a powerful interoperability mechanism with OWL, allowing the user to retrieve information from OWL ontologies, and build rule-based reasoning on top of OWL ontologies. The system is already used in a number of real-world applications including agent-based systems, information extraction, and text classification.

Semantic enrichment of enterprise modelling supported by ontologies

Enterprise modelling and ontology are two separated fields of research. On the one hand, there exists various enterprise modelling languages developed since twenty years, that are mostly considered on a syntactic basis. On the other hand, ontologies have been elaborated, which aim to formally define concepts within a specific domain in order to avoid ambiguities of understanding. Some problems of application and use of enterprise modelling languages raised come from the lack of semantic. So, semantic enrichment of these languages is becoming an important topic in enterprise integration and interoperability areas and ontology can be a solution to bring semantics.

Constructing an enterprise ontology for an automotive supplier

This paper presents experiences and conclusions from ontology engineering applied in the automotive suppliers domain. The work focuses on construction of enterprise ontologies to support structuring of enterprise information and knowledge management. Two methods for ontology construction, developed by previous research activities, were used in parallel when developing an ontology for a company in automotive supplier industries. One method is automatic and the other method is a manual approach. A conclusion was that the developed ontologies complemented each other well and therefore the decision was made to merge them for use in the project. The resulting ontology will now be used in several pilot applications.

Ontology-based knowledge management for joint venture projects

When enterprises engage in strategic joint venture projects, communication, knowledge sharing and management issues are inevitable and complex problems. Problems relating to communication, knowledge sharing and management issues generally occur in more than one phase of joint venture projects and involve various different domains. This study reviews issues related to knowledge management in the context of joint ventures (JV) from both macro and micro perspectives by using an ontology-based approach to analyze complex knowledge management (KM) issues in the context of the Integrated Circuit (IC) industry. This study presents a framework for an ontology-based model to analyze the knowledge management processing of joint ventures in the IC industry, and uses the IC foundry industry as an example to explore implementation issues. This framework uses a conceptual enterprise ontology (EO) model and domains of EO to analyze the process of EO. Moreover, data from the IC foundry industry is used as a case study. This study aimed to assist managers in increasing the possibility of success in dealing with complicated JV projects.

Virtual inter-firm collaborative framework—An IC foundry merger/acquisition project

This study proposes a novel virtual collaborative framework to assist in analyzing and designing logistical processes for inter-firm merger/acquisitions in the IC foundry industry. To elucidate the different but correlated issues when developing the framework, enterprise ontology theory is adopted to deal with knowledge-sharing problems involving merger/acquisition partners. Additionally, several analytical methods, including collaborative production lifecycle chain diagram, process chain diagram and unified modeling language (UML), are utilized for analyzing issues at different levels to design a virtual prototype for mergers/acquisitions.

An ontology oriented approach for knowledge criticality analysis

Knowledge criticality analysis is an important economic stake for enterprise. As a matter of fact, managers and decision-makers must be able to identify as quickly as possible what aspects of knowledge are critical or could be critical in a close future. This paper presents a methodology provided with tools for knowledge criticality analysis based on a competency oriented approach for the enterprise. This methodology relies first on enterprise ontology building and then on knowledge cartography. The enterprise ontology represents knowledge about competencies, jobs and projects when knowledge cartography allows to visualise the critical information mapped on the ontology.

The Timeless Way of Building REA Enterprise Systems

In a continuously changing business environment, the need for enterprise systems that are more adaptable has been recognized by many. Several solutions are being suggested to improve the adaptability of enterprise systems, including service-oriented architectures, model-driven architectures, and reflective architectures. In this paper, we propose a timeless way of building enterprise systems that employs a reflective architecture with integrated Resource-Event-Agent (REA) enterprise ontology specifications. We show how the explicit recording of enterprise schema descriptions results in enterprise systems with increased adaptability. In addition, we demonstrate how explicitly recorded ontological specifications can further increase application reusability. We validate our research with a prototype system.

Semantic enterprise application integration standards

This paper investigates the potential of the Semantic Web technologies to support a semantic-based Enterprise Application Integration (EAI) standards architecture. We give detailed information of the support that these technologies and the underlying Description Logics (DL) formalism provide for the integration task. Our main aim is to assess the potential impact of these emerging technologies on industrial interoperability efforts. In addition to that effect, we plan to use this advanced EAI standards architecture as an experimental framework in which the Semantic Web technologies are evaluated on realistic enterprise integration problems. We illustrate novel capabilities beyond the existing syntactic integration approaches when managing multiple enterprise ontologies derived from a common ontology.

Infrastructure for a clinical-decision-intelligence system

Clinical decision intelligence (CDI) is an emerging area in health care, covering a broad range of subjects, from clinical data integration and data analysis to knowledge management and application development. The goal of CDI systems is to improve health-care quality and reduce costs through the discovery, management, and application of clinical intelligence from heterogeneous and rapidly expanding data sources. These sources include data from clinical practice, nursing, health-care management, health-care administration, and medical research. In this paper, we discuss the functional requirements and reference architecture for CDI systems and their clinical applications. This architecture includes an integrated framework for managing the entire CDI process, a standardized enterprise ontology management system, and a clinical knowledge representation platform. The CDI approach has the potential to transform the health-care management process through the integration of business intelligence, business rule management, and business process management in a clinical setting, and to help health-care organizations move closer to an on demand model.

CONSTRUCTING AN ENTERPRISE ONTOLOGY FOR AN AUTOMOTIVE SUPPLIER

This paper presents experiences and conclusions from ontology engineering applied in the automotive suppliers domain. The work focuses on construction of enterprise ontologies to support structuring of enterprise information and knowledge management. Two methods for ontology construction, developed by previous research activities, were used in parallel when developing an ontology for a company in automotive supplier industries. One method is automatic and the other method is a manual approach. A conclusion was that the developed ontologies complemented each other well and therefore the decision was made to combine them for use in the project. The resulting ontology will now be used in the coming development of a pilot application.